GISRUK 2025
Sustrans Scotland
CycleStreets Ltd, Cambridge, UK
April 23, 2025
Evidence on street networks and their potential changes under future scenarios is crucial for active travel planning. However, most active travel models rely on oversimplified street representations, using single variables like ‘quietness’, neglecting key factors such as footway widths. This paper introduces new methods for classifying street networks for active travel, integrating diverse datasets from OpenStreetMap and official sources. Implemented in open source software packages osmactive and anime, these methods are scalable and reproducible. The results are showcased in a web application hosted at www.npt.scot, demonstrating how geographic data science can drive high-impact research.
network analysis, transport planning, OpenStreetMap, active travel, reproducible research
Web app deployed at npt.scot for cycle network planning in Scotland.
The bible of Scottish cycling infrastructure planning.
Available at transport.gov.scot.
osmactive R package and anime Rust crate.